962 resultados para Generation of 1837
Resumo:
A better understanding of effects after digestate application on plant community, soil microbial community as well as nutrient and carbon dynamics is crucial for a sustainable grassland management and the prevention of species and functional diversity loss. The specific research objectives of the thesis were: (i) to investigate effects after digestate application on grass species and soil microbial community, especially focussing on nitrogen dynamic in the plant-soil system and to examine the suitability of the digestate from the “integrated generation of solid fuel and biogas from biomass” (IFBB) system as fertilizer (Chapter 3). (ii) to investigate the relationship between plant community and functionality of soil microbial community of extensively managed meadows, taking into account temporal variations during the vegetation period and abiotic soil conditions (Chapter 4). (iii) to investigate the suitability of IFBB-concept implementation as grassland conservation measure for meadows and possible associated effects of IFBB digestate application on plant and soil microbial community as well as soil microbial substrate utilization and catabolic evenness (Chapter 5). Taken together the results indicate that the digestate generated during the IFBB process stands out from digestates of conventional whole crop digestion on the basis of higher nitrogen use efficiency and that it is useful for increasing harvestable biomass and the nitrogen content of the biomass, especially of L. perenne, which is a common species of intensively used grasslands. Further, a medium application rate of IFBB digestate (50% of nitrogen removed with harvested biomass, corresponding to 30 50 kg N ha-1 a-1) may be a possibility for conservation management of different meadows without changing the functional above- and belowground characteristic of the grasslands, thereby offering an ecologically worthwhile alternative to mulching. Overall, the soil microbial biomass and catabolic performance under planted soil was marginally affected by digestate application but rather by soil properties and partly by grassland species and legume occurrence. The investigated extensively managed meadows revealed a high soil catabolic evenness, which was resilient to medium IFBB application rate after a three-year period of application.
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Protecting the quality of children growth and development becomes a supreme qualification for the betterment of a nation. Double burden child malnutrition is emerging worldwide which might have a strong influence to the quality of child brain development and could not be paid-off on later life. Milk places a notable portion during the infancy and childhood. Thus, the deep insight on milk consumption pattern might explain the phenomenon of double burden child malnutrition correlated to the cognitive impairments. Objective: Current study is intended (1) to examine the current face of Indonesian double burden child malnutrition: a case study in Bogor, West Java, Indonesia, (2) to investigate the association of this phenomenon with child brain development, and (3) to examine the contribution of socioeconomic status and milk consumption on this phenomenon so that able to formulate some possible solutions to encounter this problem. Design: A cross-sectional study using a structured coded questionnaire was conducted among 387 children age 5-6 years old and their parents from 8 areas in Bogor, West-Java, Indonesia on November 2012 to December 2013, to record some socioeconomic status, anthropometric measurements, and history of breast feeding. Diet and probability of milk intake was assessed by two 24 h dietary recalls and food frequency questionnaire (FFQ). Usual daily milk intake was calculated using Multiple Source Method (MSM). Some brain development indicators (IQ, EQ, learning, and memory ability) using Projective Multi-phase Orientation method was also executed to learn the correlation between double burden child malnutrition and some brain development indicator. Results and conclusions: A small picture of child double burden malnutrition is shown in Bogor, West Java, Indonesia, where prevalence of Severe Acute Malnutrition (SAM) is 27.1%, Moderate Acute Malnutrition (MAM) is 24.9%, and overnutrition is 7.7%. This phenomenon proves to impair the child brain development. The malnourished children, both under- and over- nourished children have significantly (P-value<0.05) lower memory ability compared to the normal children (memory score, N; SAM = 45.2, 60; MAM = 48.5, 61; overweight = 48.4, 43; obesity = 47.9, 60; normal = 52.4, 163). The plausible reasons behind these evidences are the lack of nutrient intake during the sprout growth period on undernourished children or increasing adiposity on overnourished children might influence the growth of hippocampus area which responsible to the memory ability. Either undernutrition or overnutrition, the preventive action on this problem is preferable to avoid ongoing cognitive performance loss of the next generation. Some possible solutions for this phenomenon are promoting breast feeding initiation and exclusive breast feeding practices for infants, supporting the consumption of a normal portion of milk (250 to 500 ml per day) for children, and breaking the chain of poverty by socioeconomic improvement. And, the national food security becomes the fundamental point for the betterment of the next. In the global context, the causes of under- and over- nutrition have to be opposed through integrated and systemic approaches for a better quality of the next generation of human beings.
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The demand for biomass for bioenergy has increased rapidly in industrialized countries in the recent years. Biogenic energy carriers are known to reduce CO2 emissions. However, the resource-inefficient production of biomass often caused negative impacts on the environment, e.g. biodiversity losses, nitrate leaching, and erosion. The detrimental effects evolved mainly from annual crops. Therefore, the aim of modern bioenergy cropping systems is to combine yield stability and environmental benefits by the establishment of mixed-cropping systems. A particular emphasis is on perennial crops which are perceived as environmentally superior to annual crops. Agroforestry systems represent such mixed perennial cropping systems and consist of a mix of trees and arable crops or grassland within the same area of land. Agroforestry practices vary across the globe and alley cropping is a type of agroforestry system which is well adapted to the temperate zone, with a high degree of mechanization. Trees are planted in rows and crops are planted in the alleyways, which facilitates their management by machinery. This study was conducted to examine a young alley cropping system of willows and two grassland mixtures for bioenergy provision under temperate climate conditions. The first part of the thesis identified possible competition effects between willows and the two grassland mixtures. Since light seemed to be the factor most affecting the yield performance of the understory in temperate agroforestry systems, a biennial in situ artificial shade experiment was established over a separate clover-grass stand to quantify the effects of shade. Data to possible below- and aboveground interactions among willows and the two grassland mixtures and their effects on productivity, sward composition, and quality were monitored along a tree-grassland interface within the alleys. In the second part, productivity of the alley cropping system was examined on a triennial time frame and compared to separate grassland and willow stands as controls. Three different conversion technologies (combustion of hay, integrated generation of solid fuel and biogas from biomass, whole crop digestion) were applied to grassland biomass as feedstock and analyzed for its energetic potential. The energetic potential of willow wood chips was calculated by applying combustion as conversion technique. Net energy balances of separate grassland stands, agroforestry and pure willow stands evaluated their energy efficiency. Results of the biennial artificial shade experiment showed that severe shade (80 % light reduction) halved grassland productivity on average compared to a non-shaded control. White clover as heliophilous plant responded sensitively to limited radiation and its dry matter contribution in the sward decreased with increasing shade, whereas non-leguminous forbs (mainly segetal species) benefited. Changes in nutritive quality could not be confirmed by this experiment. Through the study on interactions within the alleys of the young agroforestry system it was possible to outline changes of incident light, soil temperature and sward composition of clover-grass along the tree-grassland interface. Nearly no effects of trees on precipitation, soil moisture and understory productivity occurred along the interface during the biennial experiment. Considering the results of the productivity and the net energy yield alley cropping system had lower than pure grassland stands, irrespective of the grassland seed mixture or fertilization, but was higher than that for pure willow stands. The comparison of three different energetic conversion techniques for the grassland biomass showed highest net energy yields for hay combustion, whereas the integrated generation of solid fuel and biogas from biomass (IFBB) and whole crop digestion performed similarly. However, due to the low fuel quality of hay, its direct combustion cannot be recommended as a viable conversion technique, whereas IFBB fuels were of a similar quality to wood chip from willow.
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Mesh generation is an important step inmany numerical methods.We present the “HierarchicalGraphMeshing” (HGM)method as a novel approach to mesh generation, based on algebraic graph theory.The HGM method can be used to systematically construct configurations exhibiting multiple hierarchies and complex symmetry characteristics. The hierarchical description of structures provided by the HGM method can be exploited to increase the efficiency of multiscale and multigrid methods. In this paper, the HGMmethod is employed for the systematic construction of super carbon nanotubes of arbitrary order, which present a pertinent example of structurally and geometrically complex, yet highly regular, structures. The HGMalgorithm is computationally efficient and exhibits good scaling characteristics. In particular, it scales linearly for super carbon nanotube structures and is working much faster than geometry-based methods employing neighborhood search algorithms. Its modular character makes it conducive to automatization. For the generation of a mesh, the information about the geometry of the structure in a given configuration is added in a way that relates geometric symmetries to structural symmetries. The intrinsically hierarchic description of the resulting mesh greatly reduces the effort of determining mesh hierarchies for multigrid and multiscale applications and helps to exploit symmetry-related methods in the mechanical analysis of complex structures.
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The registration of pre-operative volumetric datasets to intra- operative two-dimensional images provides an improved way of verifying patient position and medical instrument loca- tion. In applications from orthopedics to neurosurgery, it has a great value in maintaining up-to-date information about changes due to intervention. We propose a mutual information- based registration algorithm to establish the proper align- ment. For optimization purposes, we compare the perfor- mance of the non-gradient Powell method and two slightly di erent versions of a stochastic gradient ascent strategy: one using a sparsely sampled histogramming approach and the other Parzen windowing to carry out probability density approximation. Our main contribution lies in adopting the stochastic ap- proximation scheme successfully applied in 3D-3D registra- tion problems to the 2D-3D scenario, which obviates the need for the generation of full DRRs at each iteration of pose op- timization. This facilitates a considerable savings in compu- tation expense. We also introduce a new probability density estimator for image intensities via sparse histogramming, de- rive gradient estimates for the density measures required by the maximization procedure and introduce the framework for a multiresolution strategy to the problem. Registration results are presented on uoroscopy and CT datasets of a plastic pelvis and a real skull, and on a high-resolution CT- derived simulated dataset of a real skull, a plastic skull, a plastic pelvis and a plastic lumbar spine segment.
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Learning contents adaptation has been a subject of interest in the research area of the adaptive hypermedia systems. Defining which variables and which standards can be considered to model adaptive content delivery processes is one of the main challenges in pedagogical design over e-learning environments. In this paper some specifications, architectures and technologies that can be used in contents adaptation processes considering characteristics of the context are described and a proposal to integrate some of these characteristics in the design of units of learning using adaptation conditions in a structure of IMS-Learning Design (IMS-LD) is presented. The key contribution of this work is the generation of instructional designs considering the context, which can be used in Learning Management Systems (LMSs) and diverse mobile devices
Resumo:
A causa de los conflictos armados, como el de Colombia, se han desplazado por la fuerza a millones de personas, entre ellas una importante parte de la población infantil. Este estudio tuvo como objetivo evaluar la salud mental de los niños desplazados internos en edad preescolar en Bogotá Colombia, e identificar los determinantes de la salud mental en estos niños. Métodos: Estudio transversal realizado entre 279 niños que asisten a cuatro jardines infantiles en un barrio marginal de Bogotá. La salud mental infantil se evaluó con el instrumento validado de Comportamiento Infantil (CBCL) 1,5-5 años, aplicados a padres y cuidadores. Se realizo un análisis univariado y multivariado de regresión logística para evaluar la asociación entre el desplazamiento y la salud mental de los niños y para identificar las relaciones con la salud mental en los niños desplazados. Resultados: los Niños desplazados (n = 90) se identificaron con más frecuencia sobre los puntos de corte límite para las escalas CBCL que los no desplazados (n = 189) (por ejemplo, problemas totales 46,7 vs 22,8%;p \ 0,001). La asociación entre el desplazamiento y la presencia de problemas CBCL totales se mantuvo después del ajuste por factores socio-demográficos (OR Ajustado 3.3 del 95%: 1,5; 6,9). Donde la salud mental del cuidador explica en parte la asociación. En los niños desplazados, la salud mental del cuidador (p \ 0,01) y el funcionamiento familiar (p \ 0,01) se asociaron independientemente con la salud mental de los niños. La exposición a eventos traumáticos y el apoyo social también se asociaron con la salud mental del niño, sin embargo, las asociaciones no fueron independientes. Conclusión: En este barrio marginal de Bogotá, los niños en edad preescolar registrados como desplazados internos presentan peor salud mental que los no desplazados. El funcionamiento familiar y la salud mental del cuidador fueron fuerte e independientemente asociados con la salud mental de los niños y niñas desplazados.
Resumo:
Educating health professionals implies the challenge of creating and developing an inquiring mind, ready to be in a state of permanent questioning. For this purpose, it is fundamental to generate a positive attitude toward the generation of knowledge and science. Objective: to determine the attitude toward science and the scientific method in undergraduate students of health sciences. Materials and methods: a cross-sectional study was made by applying a self-administered survey, excluding those who were transferred from other universities and repeated. The attitude toward science and the scientific method were valued using the scale validated and published by Hren, which contains three domains: value of scientific knowledge, value of scientific methodology, and value of science for health professions. Results: 362 students were included, 86,6% of them graded the attitude toward scientific knowledge above 135 points, neutral scale value. Similar scores were registered in the domains value of scientific knowlede for the human dimension of the students and value of science for health professions. 91,4% of the students graded the value of scientific methodology below 48 points. Conclusions: the favorable attitude of the students can be explained by the contact that they have with the scientific method since the beginning of their studies and its concordance with the evolution of science. The domain value of scientific methodology obtained the lowest grade on the part of the students, which could be related to the lack of knowledge about scientific methodology.
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This paper presents a case study that explores the advantages that can be derived from the use of a design support system during the design of wastewater treatment plants (WWTP). With this objective in mind a simplified but plausible WWTP design case study has been generated with KBDS, a computer-based support system that maintains a historical record of the design process. The study shows how, by employing such a historical record, it is possible to: (1) rank different design proposals responding to a design problem; (2) study the influence of changing the weight of the arguments used in the selection of the most adequate proposal; (3) take advantage of keywords to assist the designer in the search of specific items within the historical records; (4) evaluate automatically the compliance of alternative design proposals with respect to the design objectives; (5) verify the validity of previous decisions after the modification of the current constraints or specifications; (6) re-use the design records when upgrading an existing WWTP or when designing similar facilities; (7) generate documentation of the decision making process; and (8) associate a variety of documents as annotations to any component in the design history. The paper also shows one possible future role of design support systems as they outgrow their current reactive role as repositories of historical information and start to proactively support the generation of new knowledge during the design process
Resumo:
A dry three-dimensional baroclinic life cycle model is used to investigate the role of turbulent fluxes of heat and momentum within the boundary layer on mid-latitude cyclones. Simulations are performed of life cycles for two basic states, both with and without turbulent fluxes. The different basic states produce cyclones with contrasting frontal and mesoscale-flow structures. The analysis focuses on the generation of potential-vorticity (PV) in the boundary layer and its subsequent transport into the free troposphere. The dynamic mechanism through which friction mitigates a barotropic vortex is that of Ekman pumping. This has often been assumed to be also the dominant mechanism for baroclinic developments. The PV framework highlights an additional, baroclinic mechanism. Positive PV is generated baroclinically due to friction to the north-east of a surface low and is transported out of the boundary layer by a cyclonic conveyor belt flow. The result is an anomaly of increased static stability in the lower troposphere which restricts the growth of the baroclinic wave. The reduced coupling between lower and upper levels can be sufficient to change the character of the upper-level evolution of the mature wave. The basic features of the baroclinic damping mechanism are robust for different frontal structures, with and without turbulent heat fluxes, and for the range of surface roughness found over the oceans.
Resumo:
Satellite-based rainfall monitoring is widely used for climatological studies because of its full global coverage but it is also of great importance for operational purposes especially in areas such as Africa where there is a lack of ground-based rainfall data. Satellite rainfall estimates have enormous potential benefits as input to hydrological and agricultural models because of their real time availability, low cost and full spatial coverage. One issue that needs to be addressed is the uncertainty on these estimates. This is particularly important in assessing the likely errors on the output from non-linear models (rainfall-runoff or crop yield) which make use of the rainfall estimates, aggregated over an area, as input. Correct assessment of the uncertainty on the rainfall is non-trivial as it must take account of • the difference in spatial support of the satellite information and independent data used for calibration • uncertainties on the independent calibration data • the non-Gaussian distribution of rainfall amount • the spatial intermittency of rainfall • the spatial correlation of the rainfall field This paper describes a method for estimating the uncertainty on satellite-based rainfall values taking account of these factors. The method involves firstly a stochastic calibration which completely describes the probability of rainfall occurrence and the pdf of rainfall amount for a given satellite value, and secondly the generation of ensemble of rainfall fields based on the stochastic calibration but with the correct spatial correlation structure within each ensemble member. This is achieved by the use of geostatistical sequential simulation. The ensemble generated in this way may be used to estimate uncertainty at larger spatial scales. A case study of daily rainfall monitoring in the Gambia, west Africa for the purpose of crop yield forecasting is presented to illustrate the method.
Resumo:
Currently many ontologies are available for addressing different domains. However, it is not always possible to deploy such ontologies to support collaborative working, so that their full potential can be exploited to implement intelligent cooperative applications capable of reasoning over a network of context-specific ontologies. The main problem arises from the fact that presently ontologies are created in an isolated way to address specific needs. However we foresee the need for a network of ontologies which will support the next generation of intelligent applications/devices, and, the vision of Ambient Intelligence. The main objective of this paper is to motivate the design of a networked ontology (Meta) model which formalises ways of connecting available ontologies so that they are easy to search, to characterise and to maintain. The aim is to make explicit the virtual and implicit network of ontologies serving the Semantic Web.
The impact of deformation strain on the formation of banded clouds in idealized modeling experiments
Resumo:
Experiments are performed using an idealized version of an operational forecast model to determine the impact on banded frontal clouds of the strength of deformational forcing, low-level baroclinicity, and model representation of convection. Line convection is initiated along the front, and slantwise bands extend from the top of the line-convection elements into the cold air. This banding is attributed primarily to M adjustment. The cross-frontal spreading of the cold pool generated by the line convection leads to further triggering of upright convection in the cold air that feeds into these slantwise bands. Secondary low-level bands form later in the simulations; these are attributed to the release of conditional symmetric instability. Enhanced deformation strain leads to earlier onset of convection and more coherent line convection. A stronger cold pool is generated, but its speed is reduced relative to that seen in experiments with weaker deformational strain, because of inhibition by the strain field. Enhanced low-level baroclinicity leads to the generation of more inertial instability by line convection (for a given capping height of convection), and consequently greater strength of the slantwise circulations formed by M adjustment. These conclusions are based on experiments without a convective-parametrization scheme. Experiments using the standard or a modified scheme for this model demonstrate known problems with the use of this scheme at the awkward 4 km grid length used in these simulations. Copyright © 2008 Royal Meteorological Society
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Although climate models have been improving in accuracy and efficiency over the past few decades, it now seems that these incremental improvements may be slowing. As tera/petascale computing becomes massively parallel, our legacy codes are less suitable, and even with the increased resolution that we are now beginning to use, these models cannot represent the multiscale nature of the climate system. This paper argues that it may be time to reconsider the use of adaptive mesh refinement for weather and climate forecasting in order to achieve good scaling and representation of the wide range of spatial scales in the atmosphere and ocean. Furthermore, the challenge of introducing living organisms and human responses into climate system models is only just beginning to be tackled. We do not yet have a clear framework in which to approach the problem, but it is likely to cover such a huge number of different scales and processes that radically different methods may have to be considered. The challenges of multiscale modelling and petascale computing provide an opportunity to consider a fresh approach to numerical modelling of the climate (or Earth) system, which takes advantage of the computational fluid dynamics developments in other fields and brings new perspectives on how to incorporate Earth system processes. This paper reviews some of the current issues in climate (and, by implication, Earth) system modelling, and asks the question whether a new generation of models is needed to tackle these problems.
Resumo:
Visual exploration of scientific data in life science area is a growing research field due to the large amount of available data. The Kohonen’s Self Organizing Map (SOM) is a widely used tool for visualization of multidimensional data. In this paper we present a fast learning algorithm for SOMs that uses a simulated annealing method to adapt the learning parameters. The algorithm has been adopted in a data analysis framework for the generation of similarity maps. Such maps provide an effective tool for the visual exploration of large and multi-dimensional input spaces. The approach has been applied to data generated during the High Throughput Screening of molecular compounds; the generated maps allow a visual exploration of molecules with similar topological properties. The experimental analysis on real world data from the National Cancer Institute shows the speed up of the proposed SOM training process in comparison to a traditional approach. The resulting visual landscape groups molecules with similar chemical properties in densely connected regions.